IceCube DeepCore is an extension of the IceCube Neutrino Observatory designed to measure GeV scale atmospheric neutrino interactions for the purpose of neutrino oscillation studies. Distinguishing muon neutrinos from other flavors and reconstructing inelasticity are especially difficult tasks at GeV scale energies in IceCube DeepCore due to sparse instrumentation. Convolutional neural networks (CNNs) have been found to have better success at neutrino event reconstruction than conventional likelihood-based methods. In this contribution, we present a new CNN model that exploits time and depth translational symmetry in IceCube DeepCore data and present the model’s performance, specifically for flavor identification and inelasticity reconstruction.

The IceCube Neutrino Observatory deployed 5160 digital optical modules (DOMs) in a cubic kilometer of deep, glacial ice below the geographic South Pole, recording the Cherenkov light of passing charged particles. While the optical properties of the undisturbed ice are nowadays well understood, the properties of the refrozen drill holes still pose a challenge. From camera observations, we expect a central, strongly scattering column shadowing a part of the DOMs’ sensitive area. In MC simulation, this effect is commonly modeled as a modification to the DOMs’ angular acceptance curve, reducing the forward sensitivity of the DOMs. The associated uncertainty is a dominant detector systematic for neutrino oscillation studies as well as high-energy cascade reconstructions. Over the years, several measurements and fits of the drill holes’ optical properties and of the angular acceptance curve have been proposed, some of which are in tension. Here, we present a principle component analysis, which allows us to interpolate between all suggested scenarios, and thus provide a complete systematic variation within a unified framework at analysis level.

The IceCube Neutrino Observatory is also a very unique extensive air shower (EAS) detector, that simultaneously measures the EAS footprint on the surface and the high-energy muons in deep ice. The surface array - IceTop, comprising of ice-Cherenkov tanks, will be enhanced in the coming years with scintillation detectors and radio antennas. The hybrid detection enables the reconstruction of EAS parameters based on different underlying signal distributions. A new framework within the IceCube software allows for a flexible implementation of signal and time models for different detector components and a combination of resulting likelihood functions. The in-ice muon signal can serve as an anchor for the reconstruction of the EAS axis, resulting in an improved reconstruction resolution. Moreover, it makes it possible to reconstruct EASs with an impact point outside the IceTop array, opening a larger zenith-angle range for analyses of IceTop and in-ice coincident events. In this contribution, we present the capabilities of the combined reconstruction for different classes of EAS events with various detector configurations.

Currently, an upgrade consisting of seven densely instrumented strings in the center of the volume of the IceCube detector with new digital optical modules (DOMs) is being built. On each string, DOMs will be regularly spaced with a vertical separation of 3 m between depths of 2160 m and 2430 m below the surface of the ice, which is a denser configuration compared to the existing DOMs of IceCube detector.

For a precise calibration of the IceCube Upgrade it is important to understand the properties of the ice, both inside and surrounding the deployment holes. LEDs and Camera systems, which are developed and produced at Sungkyunkwan university, are installed in every single DOM to measure these properties. For these calibration measurements, a new simulation framework, which produces expected images from various geometric and optical variables has been developed and images produced from the simulation are expected to be used to develop an analysis framework for the IceCube Upgrade camera calibration system and for the design of the IceCube Gen2 camera system.

IceCube has reported evidence for neutrino emission from the Seyfert-II galaxy NGC 1068 and the blazar TXS 0506+056. The former was identified in a time-integrated search, and the latter using time-dependent and multi-messenger methods. A natural question is: are sources identified in time-integrated searches consistent with a steady neutrino source? We present a non-parametric method, TAUNTON, to answer this question. Motivated by the Cramér-von Mises test, TAUNTON is an unbinned single-hypothesis method to identify deviations in neutrino data from the steady hypothesis. An advantage of TAUNTON is that it is sensitive to arbitrary deviations from the steady hypothesis. Here we present results of TAUNTON applied to a 8.7 year data-set of muon neutrino track events; the same data used to identify NGC 1068 at 4.2σ. We use TAUNTON on 51 objects, a subset (with >4 signal neutrinos) of the 110 objects studied in the NGC 1068 publication. We set a threshold of 3σ pre-trial to identify sources inconsistent with the steady hypothesis. TAUNTON reports a p-value of 0.9 for NGC 1068, consistent with the steady hypothesis. Using the time integrated fit, data for TXS 0506+056 is consistent with the steady hypothesis at 1.7σ. Time variability is not identified for TXS 0506+056 because there are few neutrino events.

The surface component of the IceCube Neutrino Observatory, IceTop, consists of an array of ice-Cherenkov tanks measuring the electromagnetic signal as well as low-energy (∼ GeV) muons from cosmic-ray air showers. In addition, accompanying high-energy (above a few 100 GeV) muons can be observed in coincidence in the deep in-ice detector. A combined measurement of the low- and high-energy muon content is of particular interest for tests of hadronic interaction models as well as for cosmic-ray mass discrimination. However, since IceTop does not feature dedicated muon detectors, an estimation of the low-energy muon component of individual air showers is challenging. In this work, a two-component lateral distribution function (LDF), using separate descriptions for the electromagnetic and muon lateral distributions of the detector signals, is introduced as a new approach for the estimation of low-energy muons in air showers on an event-by-event basis. The principle of the air-shower reconstruction using the two-component LDF, as well as its reconstruction performance with respect to primary energy and number of low-energy muons will be discussed.

The IceTop surface detector of the IceCube Neutrino Observatory measures extensive air showers (EAS). Coincident signals in both tanks of an IceTop station result primarily from the electromagnetic component of the EAS, and events which trigger at least 5 stations correspond to energies roughly above the knee, with an energy threshold and reconstruction behavior that changes over time as snow accumulates above the array. We present a status report of an analysis of ≥ 5-station events in IceTop from 2011-2021, which will be used to measure the all-particle spectrum of cosmic rays in the transition region from galactic to extragalactic sources up to EeV range, using updated simulations and improved treatments of snow attenuation. In particular, a snow model has been developed which takes the non-attenuating muon content of tank signals, as well as their saturation behavior, into account.

The interaction of cosmic rays with the solar atmosphere generates a secondary flux of mesons that decay into photons and neutrinos – the so-called solar atmospheric flux. Although the gamma-ray component of this flux has been observed in Fermi-LAT and HAWC Observatory data, the neutrino component remains undetected. The energy distribution of those neutrinos follows a soft spectrum that extends from the GeV to the multi-TeV range, making large Cherenkov neutrino telescopes a suitable for probing this flux. In this contribution, we will discuss current progress of a search for the solar neutrino flux by the IceCube Neutrino Observatory using all available data since 2011. Compared to the previous analysis which considered only high-energy muon neutrino tracks, we will additionally consider events produced by all flavors of neutrinos down to GeV-scale energies. These new events should improve our analysis sensitivity since the flux falls quickly with energy. Determining the magnitude of the neutrino flux is essential, since it is an irreducible background to indirect solar dark matter searches.

The IceCube realtime alert system has been operating since 2016. It provides prompt alerts on high-energy neutrino events to the astroparticle physics community. The localization regions for the incoming direction of neutrinos are published through NASA’s Gamma-ray Coordinate Network (GCN). The IceCube realtime system consists of infrastructure dedicated to the selection of alert events, the reconstruction of their topology and arrival direction, the calculation of directional uncertainty contours and the distribution of the event information through public alert networks. Using a message-based workflow management system, a dedicated software (SkyDriver) provides a representational state transfer (REST) interface to parallelized reconstruction algorithms. In this contribution, we outline the improvements of the internal infrastructure of the IceCube realtime system that aims to streamline the internal handling of neutrino events, their distribution to the SkyDriver interface, the collection of the reconstruction results as well as their conversion into human- and machine-readable alerts to be publicly distributed through different alert networks. An approach for the long-term storage and cataloging of alert events according to findability, accessibility, interoperability and reusability (FAIR) principles is outlined.

A precise understanding of the optical properties of the instrumented Antarctic ice sheet is crucial to the performance of the IceCube Neutrino Observatory, a cubic-kilometer Cherenkov array of 5,160 digital optical modules (DOMs) deployed in the deep ice below the geographic South Pole.

We present an update to the description of the ice tilt, which describes the undulation of layers of constant optical properties as a function of depth and transverse position in the detector. To date, tilt modeling has been based solely on stratigraphy measurements performed by a laser dust logger during the deployment of the array. We now show that it can independently be deduced using calibration data from LEDs located in the DOMs. The new fully volumetric tilt model not only confirms the magnitude of the tilt along the direction orthogonal to the ice flow obtained from prior dust logging, but also includes a newly discovered tilt component along the flow.